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IoT & IndustrialEnergy
AquaWarn
AI Smart Flood Detector based on nRF9160
LTE-M flood sensor that measures water depth and predicts flash flood risk using local rainfall models.
Water Level Accuracy
±5mm
Battery Life
5+ Years
AquaWarn
Client
A municipal flood management authority deploying an early warning sensor network across urban drainage basins and known flood-risk areas.
Challenge
Building a submersible, battery-operated sensor that can measure water depth with millimeter accuracy, survive complete submersion, and provide early flash flood warnings.
Product Concept & Architecture
The Nordic nRF9160 LTE-M SiP reads an MS5837 high-precision pressure sensor (depth resolution 2mm) and a tipping bucket rain gauge. An overmolded IP69K housing withstands permanent submersion.
Engineering Solution
Barometric pressure compensation is done using a co-located BME280 (subtracting atmospheric pressure from total pressure to derive water depth). If depth exceeds 50mm and rainfall rate exceeds 25mm/h, an immediate flood alert is sent via LTE-M.
Result
±5mm water depth accuracy. 5+ year battery life. Provided 20-minute advance flash flood warning during monsoon season pilot.
Deep Tech FAQ
What makes the AI Smart Flood Detector based on nRF9160 unique?+
The AI Smart Flood Detector based on nRF9160 leverages custom hardware and edge AI to deliver industry-leading performance and efficiency.
What are the core technical benefits?+
Key benefits include low power consumption, real-time processing, robust connectivity, and a compact form factor tailored for deployment.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying methodology is modular and can be retargeted for various applications with minimal redesign.
Project Profile
Services Delivered
Hardware DesignEmbedded SoftwareRF Design
Core Technologies
LTE-M/NB-IoTGNSSZephyr RTOS
Silicon & Vendors
NordicSTMicroelectronics
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